Considering Culture-Specific Occupant Behaviour in Energy Performance Evaluation: A Case Study of Residential Houses in Riyadh, Saudi Arabia

Energy consumption prediction is a critical aspect of home design that can help homeowners manage energy use. At present, the performance gap between energy consumption prediction and actual energy use could reach two to five times higher than current predicted performance rates (Zou, Wagle & Alam 2019). Lack of information about the specific factors that control energy use is a main contributor to energy performance gaps (Yoshino, Hong & Nord 2017). However, research has shown that human behaviour significantly impacts energy performance gaps, even more than building design.
Recent technological advances have led to the development of energy simulation software that helps predict energy use. The software includes various inputs to support energy consumption predictions. This study aims to address the lack of information related to Saudi cultural occupant behaviour in an effort to enhance load schedule inputs into simulation software to improve energy use predictions. This research focuses on single-family houses in Riyadh, Saudi Arabia.
For this study, a mixed-methods approach was used. A combination of both quantitative and qualitative methods allows for an in-depth exploration and understanding of cultural behaviour. In total, ten case studies were used and 1600 survey responses were collected from participants using face-to-face surveys and online forms. The researcher found that privacy is one of the main factors that shape Saudi culture. This is reflected in the behaviour of occupants, house design, and circulation. To prevent circulation overlap between guests and family members, houses are divided into three main zones: a male guest zone, a female guest zone, and a family zone. This research addresses the gap in the literature regarding unique behaviour for targeted zones. The experimental study showed that guest zones covered 30% to 40% of the total home area. Each of these zones had unique time-use behaviour. Results of data analysis found that the average time-use of the guest zones was 36 days per year. The time-use data (TUD) survey results were used to develop an occupancy prediction tool using Random Forest. The tool predicted the time-use for the male guest zone, the female guest zone, and the living halls across five case studies. The five case studies were used to evaluate the occupancy prediction tool and test its applications in energy simulation. Without considering the cultural behaviour, experiment results show the gap between energy prediction output and real energy use could reach as high as 52%. After applying the prediction tool, the gap was reduced to a difference of 4%.
This study focuses on the single-family who lives in a detached house in the capital of Saudi Arabia, Riyadh. It considers the cultural behaviour related to occupants’ use of guest zones in their homes. The research did not consider other behaviour that may be driven by Saudi culture, such as the size or the time-use of windows, which may also impact energy consumption. There is potential for future researchers to investigate the impact of culture on other features in the house, to collect more data considering the other building and family types in Riyadh or other cities in the country, and to validate the model and the impact of the cultural behaviour on the energy consumption using more case studies.